Median regression from twice censored data
Document Type
Article
Publication Date
1-1-2021
Abstract
An adjusted least absolute deviation estimating function, founded on the inverse (probability of) censoring weighted approach, is proposed. Covariate-free left and right censoring is assumed. When left censoring is absent, the proposed estimating function reduces to its right-censored counterpart. Consistency and asymptotic normality of the estimator of the regression parameter are derived. Finite sample performance is investigated via simulations. Application of the proposed method is illustrated using some synthetic data sets.
Identifier
85092054970 (Scopus)
Publication Title
Statistics and Probability Letters
External Full Text Location
https://doi.org/10.1016/j.spl.2020.108955
ISSN
01677152
Volume
168
Recommended Citation
Subramanian, Sundarraman, "Median regression from twice censored data" (2021). Faculty Publications. 4411.
https://digitalcommons.njit.edu/fac_pubs/4411
